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DP-300 Practice Question: Monitor, configure, and optimize database resources

Which THREE metrics should you monitor to proactively detect potential performance issues in an Azure SQL Database?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Log IO percentage (sys.dm_db_resource_stats)

Options A, D, and E are correct. Log IO percentage (A) from sys.dm_db_resource_stats indicates transaction log throughput bottlenecks. Wait statistics (D) from sys.dm_os_wait_stats show where queries are waiting, revealing contention or resource pressure. Query Store (E) tracks query plan regressions and performance degradation over time. Option B is incorrect because log backup frequency affects recovery point objectives (RPO), not proactive performance monitoring. Option C is incorrect because database size and growth rate relate to storage capacity planning, not real-time performance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Log IO percentage (sys.dm_db_resource_stats)

    Why this is correct

    High log IO can indicate transaction throughput issues.

  • Log backup frequency

    Why it's wrong here

    Affects RPO, not performance.

  • Database size and growth rate

    Why it's wrong here

    Indicates storage usage, not performance.

  • Wait statistics (sys.dm_os_wait_stats)

    Why this is correct

    Shows database waits, key to identifying bottlenecks.

  • Query Store for query performance regressions

    Why this is correct

    Tracks plan changes and performance degradation.

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